Assistant Professor, BENG
Time series analysis in biological systems, data science
Smarr’s research focuses on time series analysis in biological systems, with an emphasis on practical information extraction for translational applications. Currently his main project is TemPredict, which brings together wearable device data from 50K people with over 1 million daily symptom reports. This massive data object is being used to identify signs of COVID-19 onset, progression, and recovery.
Before joining UC San Diego in 2020, Smarr was a postdoctoral fellow at UC Berkeley. He earned his Ph.D. at the Univeristy of Washington. Here at UC San Diego, he also holds an appointment with the Halicioglu Data Science Institute.